Lect 4 part 1 techniques for data presentation
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This document discusses different techniques for presenting data, including arrays, tables, and graphs. It provides examples of arranging data into ascending and descending order for array presentation. For tabular presentation, it describes the types and objectives of tables, and rules for tabulation. The document demonstrates arranging a sample dataset into univariate tables for sex and age, and a bivariate table crossing sex and age. Finally, it provides steps for building a frequency distribution of a quantitative variable and an example calculation.
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This document discusses frequency distributions, which summarize data by arranging it into classes and indicating how many observations fall into each class. It describes the key components of a frequency distribution, including the class, class limits, class mark, class interval, class frequency and tally marks. It provides examples of grouped frequency distributions, where the data is organized into groups, and ungrouped distributions, where the raw individual data points are listed. The objectives of a frequency distribution are to estimate population frequencies, facilitate data analysis, and allow computation of statistical measures.
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a. Class interval (ci): 4 – 8
Class Width: 4
Class Mark: 6
Class Boundary: 3.5 – 8.5
b. Class interval (ci): 35 – 44
Class Width: 9
Class Mark: 39.5
Class Boundary: 34.5 – 43.5
c. Class interval (ci): 17 – 21
Class Width: 4
Class Mark: 19
Class Boundary: 16.5 – 20.5
d. Class interval (ci): 53 – 57
Class Width: 4
Class Mark: 55
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This document discusses variables, scales of measurement, and related terminology in statistics. It defines a variable as any characteristic that differs between individuals, time, or place. Variables can be either qualitative (categorical) or quantitative (numerical) in nature. Quantitative variables are further divided into discrete variables, which have no gaps between values, and continuous variables, which have decimals. Scales of measurement include nominal, ordinal, interval, and ratio scales. The document also defines key terms like population, sample, parameter, statistic, and provides examples of variable types.
Biostatistics lec 1
This document provides an overview of an introductory biostatistics course. The course covers topics such as descriptive statistics, probability, sampling methods, and probability distributions. Lecture 1 introduces biostatistics and discusses its importance in fields like public health and medicine. Biostatistics is applied to analyze biological and health data and help address questions like disease trends, at-risk populations, and health standards. It aids decision-making under uncertainty and helps identify health issues, evaluate programs, and conduct research.
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4. Medical mycology
Bio chemo ( gsd )
GSD is a rare inherited metabolic disorder caused by deficient or defective enzymes involved in glycogen metabolism. This leads to abnormal glycogen accumulation in tissues like the liver, heart and kidneys. There are several types of GSD based on the specific enzyme deficiency. Type I is characterized by fasting hypoglycemia, hyperlipidemia and hyperuricemia due to glucose-6-phosphatase deficiency. Type II involves alpha-glucosidase deficiency causing glycogen buildup in lysosomes. Type III features abnormal glycogen storage with short branches due to glycogen debranching enzyme deficiency.
Cdc
This document provides lecture notes on communicable disease control for nursing students. It begins with an introduction that describes the high burden of communicable diseases in Ethiopia, accounting for 80% of health problems. The top leading causes of outpatient visits, admissions, and deaths are various infectious diseases like malaria, pneumonia, tuberculosis, dysentery, and meningitis. The chapter then defines key epidemiological terms and concepts. It explains that epidemiology is the study of disease frequency, distribution, and determinants in populations in order to promote health and prevent disease.
En v. h. hiu
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Chapter 7 biological hazards
This document discusses biological and physical hazards. It defines biological hazards as organic substances that threaten health, such as bacteria, viruses, fungi and toxins. It estimates 320,000 workers die annually from work-related biological exposures. Biological hazards enter the body through inhalation, absorption, ingestion, or injection. Engineering, administrative and personal protective controls are used to limit exposure. Radiation can be ionizing (x-rays, gamma rays) or non-ionizing (visible light, radio waves) with ionizing posing health risks like cancer from tissue damage. Sources of ionizing radiation include medical equipment and nuclear reactors/materials.
Chapter 6 chemical
This document provides an overview of chemical safety in the workplace. It discusses common chemicals that are hazardous, how chemicals can enter the body, and the importance of risk assessment. The key steps for risk assessment are outlined, including making an inventory, collecting safety information, assessing exposure, and implementing controls. Control methods like substitution, engineering controls, administrative controls and PPE are described. Proper chemical storage, labeling, training and emergency response are important for effective chemical management.
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Cd rom 8_optional_molecular_qc
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Biostatistics lec 2 variables and scales of measurement
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Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar lead (limb II)
4. Differentiate between intervals and segments
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1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. Chapter 3, Cardiology Explained, https://www.ncbi.nlm.nih.gov/books/NBK2214/
7. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
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Lect 4 part 1 techniques for data presentation
- 1. Techniques for Data Presentation Mohamed Hayir Tahlil Mohamud MS in Biostatistics May 11, 2021 1
- 2. Techniques of Data presentation Data can be presented into:- Array Tabular Graphical May 11, 2021 2
- 3. Array data presentation • Array is listing the data values in order of magnitude from the smallest to largest or vise verse • Array can be either • Ascending: ordering data from smallest to largest or • Descending: ordering data from largest to smallest. May 11, 2021 3
- 4. Example-1: arrange into array • The following data shows list of ages of participates in a study of smoking cessation 55 46 58 54 52 69 Ascending form: 46 52 54 55 58 69 Descending form: 69 58 55 54 52 46 May 11, 2021 4
- 5. Tabular presentation • A table s a format containing data in rows and columns. Table makes data compact, concise, and readily understandable without loosing any information of interest. Types of Tables 1. Univariate table 2. Bivariate table 3. Multivariate table May 11, 2021 5
- 6. Objectives of Tabulation To clarify the object of investigation To simplify complex data To facilitate comparison May 11, 2021 6
- 7. Rules for tabulation • The table should be simple and compact • All title, subtitle, captions should be arranged in systematic manner • The unit of measurement should be clearly defined in the table • Table should be complete and self-explanatory • A table should be attractive to draw attention o readers • Accurate process of presentation should be made • Abbreviation should be avoided May 11, 2021 7
- 8. Expmle-2: suppose we have 20 adults with their age and sex as given below arrange this data into a) Univarate tables b) Bivariate table F F F M M F M F F M F F F M F F M M M F 24 21 25 26 29 26 28 22 31 39 32 38 30 32 35 46 44 43 47 49 May 11, 2021 8
- 9. Sex Frequency Percentage Male 8 40 Female 12 60 Total 20 100 Univarate Table-1: Sex Percentage = Frequency/Total*100 May 11, 2021 9
- 10. Steps for building Frequency distribution of Quantitate variable i. step-1: Find the number of classes ii. find the range iii. Find class width Class width= range/K Range =largest value-smallest value Number of class (K)=1+3.322(Log10n) or √n May 11, 2021 10
- 11. solution Range =largest value-smallest value =49- 21=28 Number of class (K)=1+3.322(Log20)=5 or √n= √20=5 Class width= range/K=28/5=6 May 11, 2021 11
- 12. Age Frequency Percentage 21-26 6 30 27-32 6 30 33-38 2 10 39-44 3 15 45-50 3 15 Total 20 100 Univarate Table-2: Age May 11, 2021 12
- 13. Age Male Female Total 21-26 1 5 6 27-32 3 3 6 33-38 0 2 2 39-44 3 0 3 45-50 1 2 3 Total 8 12 20 Bivariate Table-1: Sex and Age May 11, 2021 13
- 14. Multivariate Table-3: Age, sex and educational level May 11, 2021 14 Educational level__ Gender__ Age Male Female Total Urban Rural Urban Rural 21-26 1 2 5 1 9 27-32 3 2 3 2 10 33-38 0 1 2 1 4 39-44 3 2 0 2 7 45-50 1 3 2 1 7 Total 8 10 12 7 37